This code reproduces the EMA intervention analyses reported in the following manuscript:

Cosme, D., Helion, C., et al. (2023) Mindful attention to alcohol can reduce cravings in the moment and consumption in daily life

load packages

library(pacman)
pacman::p_load(tidyverse, brms, ggeffects, kableExtra, tidybayes, install = TRUE)

define aesthetics

palette = c("#e64626", "#1985a1", "#4c5c68", "#FAC748")

plot_aes = theme_minimal() +
  theme(legend.position = "top",
        legend.text = element_text(size = 16),
        text = element_text(size = 18, family = "Futura Medium"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_text(color = "black"),
        axis.line = element_line(colour = "black"),
        axis.ticks.y = element_blank())

define functions

make_table = function(data) {
    data %>%
      broom.mixed::tidy(conf.int = TRUE) %>%
      filter(effect == "fixed") %>%
      mutate(term = gsub("\\(Intercept\\)", "intercept", term),
             term = gsub("regulation_expression", "signature expression", term),
             term = gsub("active_weekon", "intervention week (active)", term),
             term = gsub("active_weekoff", "intervention week (control)", term),
             term = gsub("signal_count", "signal", term),
             term = gsub(":", " x ", term),
             `b [95% CI]` = sprintf("%.2f [%.2f, %.2f]", estimate, conf.low, conf.high)) %>%
      select(term, `b [95% CI]`) %>%
      knitr::kable(digits = 2)
}

load data

merged = read.csv("../data/task_neuro_data.csv", stringsAsFactors = FALSE)
ema = read.csv("../data/ema.csv")

merge and prep for modeling

between = merged %>%
  filter(condition == "mindful attention") %>%
  select(pID, dot, trial_cond, condition) %>%
  group_by(pID, trial_cond, condition) %>%
  summarize(dot_between = mean(dot, na.rm = TRUE)) %>%
  group_by(trial_cond) %>%
  mutate(dot_between_c = scale(dot_between, scale = FALSE, center = TRUE)) %>%
  mutate(sd_dot = sd(dot_between, na.rm = TRUE),
         dot_between_std = dot_between_c / sd_dot) %>%
  select(pID, condition, trial_cond, dot_between_std) %>%
  mutate(trial_cond = sprintf("%s_expression", trial_cond)) %>%
  spread(trial_cond, dot_between_std)

ema_within = ema %>%
  left_join(., between)

descriptives

weekly drinking

ema_within %>%
  mutate(week = ifelse(signal_count %in% c(1:14), 1,
                ifelse(signal_count %in% c(15:28), 2,
                ifelse(signal_count %in% c(29:42), 3, 4)))) %>%
  group_by(pID, week) %>%
  summarize(sum = sum(drinks_number_noc, na.rm = TRUE)) %>%
  ungroup() %>%
  summarize(min = min(sum),
            max = max(sum),
            mean = mean(sum),
            sd = sd(sum)) %>%
  kable(digits = 1, format = "pandoc")
min max mean sd
0 45 5.3 7

effectiveness and individual differences: experience sampling intervention analyses (H3-4)

✅ H3a: Active intervention weeks will increase participants’ self-reported mindful attention to alcohol

✅ H3b: Mindful attention will be positively associated with decreased alcohol consumption

✅ H3c: There will be an indirect effect of intervention-related change in alcohol consumption through greater mindful attention to alcohol

✅ H4a: People with stronger signature expression would show greater increases in mindful attention to alcohol on active intervention weeks compared to control weeks

✅ H4b: People with stronger signature expression would show more negative relationships between mindful attention to alcohol and alcohol consumption

prior = c(prior(normal(0, 1), class=b))

run model

table

fit_brm_m %>%
  broom.mixed::tidy(conf.int = TRUE) %>%
  filter(effect == "fixed") %>%
  mutate(term = gsub("\\(Intercept\\)", "intercept", term),
         term = gsub("regulation_expression", "signature expression", term),
         term = gsub("active_weekon", "intervention week (active)", term),
         term = gsub("active_weekoff", "intervention week (control)", term),
         term = gsub("mindful_response", "mindful response", term),
         response = gsub("mindfulscale", "mindful response", response),
         response = gsub("drinksnumber", "number of drinks", response),
         term = gsub(":", " x ", term),
         `b [95% CI]` = sprintf("%.2f [%.2f, %.2f]", estimate, conf.low, conf.high)) %>%
  rename("outcome" = response) %>%
  select(outcome, term, `b [95% CI]`) %>%
  arrange(outcome) %>%
  knitr::kable(digits = 2, format = "pandoc")
outcome term b [95% CI]
mindfulresponse intercept -0.21 [-0.38, -0.07]
mindfulresponse intervention week (active) 0.48 [0.26, 0.73]
mindfulresponse signature expression -0.14 [-0.29, 0.02]
mindfulresponse intervention week (active) x signature expression 0.41 [0.17, 0.63]
number of drinks intercept 1.31 [0.92, 1.73]
number of drinks intervention week (active) 0.10 [-0.45, 0.66]
number of drinks signature expression -0.29 [-0.58, 0.01]
number of drinks mindful response -0.59 [-0.98, -0.17]
number of drinks signature expression x mindful response -0.33 [-0.73, 0.08]

indirect effect test

hypothesis(
  fit_brm_m,
  'b_drinksnumber_mindful_response * b_mindfulresponse_active_weekon + cor_pID__mindfulresponse_active_weekon__drinksnumber_active_weekon * sd_pID__mindfulresponse_active_weekon * sd_pID__drinksnumber_mindful_response = 0',
  class = NULL,
  seed  =  6523
)
## Hypothesis Tests for class :
##                 Hypothesis Estimate Est.Error CI.Lower CI.Upper Evid.Ratio
## 1 (b_drinksnumber_m... = 0    -0.26      0.13    -0.52    -0.01         NA
##   Post.Prob Star
## 1        NA    *
## ---
## 'CI': 90%-CI for one-sided and 95%-CI for two-sided hypotheses.
## '*': For one-sided hypotheses, the posterior probability exceeds 95%;
## for two-sided hypotheses, the value tested against lies outside the 95%-CI.
## Posterior probabilities of point hypotheses assume equal prior probabilities.

summary

summary(fit_brm_m)
##  Family: MV(gaussian, gaussian) 
##   Links: mu = identity; sigma = identity
##          mu = identity; sigma = identity 
## Formula: mindful_response ~ active_week * regulation_expression + (0 + active_week | i | pID) 
##          drinks_number ~ active_week + regulation_expression * mindful_response + (0 + active_week + mindful_response | i | pID) 
##    Data: ema_within (Number of observations: 340) 
##   Draws: 4 chains, each with iter = 500; warmup = 250; thin = 4;
##          total post-warmup draws = 250
## 
## Group-Level Effects: 
## ~pID (Number of levels: 31) 
##                                                                   Estimate
## sd(mindfulresponse_active_weekoff)                                    0.14
## sd(mindfulresponse_active_weekon)                                     0.16
## sd(drinksnumber_active_weekoff)                                       0.46
## sd(drinksnumber_active_weekon)                                        0.75
## sd(drinksnumber_mindful_response)                                     0.78
## cor(mindfulresponse_active_weekoff,mindfulresponse_active_weekon)    -0.29
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekoff)       0.02
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekoff)        0.00
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekon)       -0.08
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekon)         0.17
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)           0.27
## cor(mindfulresponse_active_weekoff,drinksnumber_mindful_response)    -0.29
## cor(mindfulresponse_active_weekon,drinksnumber_mindful_response)      0.28
## cor(drinksnumber_active_weekoff,drinksnumber_mindful_response)        0.10
## cor(drinksnumber_active_weekon,drinksnumber_mindful_response)        -0.08
##                                                                   Est.Error
## sd(mindfulresponse_active_weekoff)                                     0.08
## sd(mindfulresponse_active_weekon)                                      0.10
## sd(drinksnumber_active_weekoff)                                        0.29
## sd(drinksnumber_active_weekon)                                         0.30
## sd(drinksnumber_mindful_response)                                      0.24
## cor(mindfulresponse_active_weekoff,mindfulresponse_active_weekon)      0.40
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekoff)        0.39
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekoff)         0.39
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekon)         0.38
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekon)          0.38
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)            0.38
## cor(mindfulresponse_active_weekoff,drinksnumber_mindful_response)      0.36
## cor(mindfulresponse_active_weekon,drinksnumber_mindful_response)       0.36
## cor(drinksnumber_active_weekoff,drinksnumber_mindful_response)         0.36
## cor(drinksnumber_active_weekon,drinksnumber_mindful_response)          0.33
##                                                                   l-95% CI
## sd(mindfulresponse_active_weekoff)                                    0.01
## sd(mindfulresponse_active_weekon)                                     0.01
## sd(drinksnumber_active_weekoff)                                       0.03
## sd(drinksnumber_active_weekon)                                        0.11
## sd(drinksnumber_mindful_response)                                     0.30
## cor(mindfulresponse_active_weekoff,mindfulresponse_active_weekon)    -0.89
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekoff)      -0.75
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekoff)       -0.73
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekon)       -0.76
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekon)        -0.67
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)          -0.54
## cor(mindfulresponse_active_weekoff,drinksnumber_mindful_response)    -0.86
## cor(mindfulresponse_active_weekon,drinksnumber_mindful_response)     -0.52
## cor(drinksnumber_active_weekoff,drinksnumber_mindful_response)       -0.63
## cor(drinksnumber_active_weekon,drinksnumber_mindful_response)        -0.67
##                                                                   u-95% CI Rhat
## sd(mindfulresponse_active_weekoff)                                    0.33 1.00
## sd(mindfulresponse_active_weekon)                                     0.35 1.00
## sd(drinksnumber_active_weekoff)                                       1.12 1.00
## sd(drinksnumber_active_weekon)                                        1.31 1.00
## sd(drinksnumber_mindful_response)                                     1.28 1.01
## cor(mindfulresponse_active_weekoff,mindfulresponse_active_weekon)     0.60 1.00
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekoff)       0.73 1.00
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekoff)        0.73 1.00
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekon)        0.66 1.00
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekon)         0.81 1.00
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)           0.85 1.00
## cor(mindfulresponse_active_weekoff,drinksnumber_mindful_response)     0.51 1.00
## cor(mindfulresponse_active_weekon,drinksnumber_mindful_response)      0.85 1.01
## cor(drinksnumber_active_weekoff,drinksnumber_mindful_response)        0.74 1.00
## cor(drinksnumber_active_weekon,drinksnumber_mindful_response)         0.56 1.00
##                                                                   Bulk_ESS
## sd(mindfulresponse_active_weekoff)                                     632
## sd(mindfulresponse_active_weekon)                                      600
## sd(drinksnumber_active_weekoff)                                        748
## sd(drinksnumber_active_weekon)                                         551
## sd(drinksnumber_mindful_response)                                      541
## cor(mindfulresponse_active_weekoff,mindfulresponse_active_weekon)      741
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekoff)        817
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekoff)        1000
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekon)         626
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekon)          801
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)            791
## cor(mindfulresponse_active_weekoff,drinksnumber_mindful_response)      443
## cor(mindfulresponse_active_weekon,drinksnumber_mindful_response)       717
## cor(drinksnumber_active_weekoff,drinksnumber_mindful_response)         920
## cor(drinksnumber_active_weekon,drinksnumber_mindful_response)          768
##                                                                   Tail_ESS
## sd(mindfulresponse_active_weekoff)                                     769
## sd(mindfulresponse_active_weekon)                                      686
## sd(drinksnumber_active_weekoff)                                        814
## sd(drinksnumber_active_weekon)                                         459
## sd(drinksnumber_mindful_response)                                      342
## cor(mindfulresponse_active_weekoff,mindfulresponse_active_weekon)      917
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekoff)        802
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekoff)         992
## cor(mindfulresponse_active_weekoff,drinksnumber_active_weekon)         738
## cor(mindfulresponse_active_weekon,drinksnumber_active_weekon)          852
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)            842
## cor(mindfulresponse_active_weekoff,drinksnumber_mindful_response)      738
## cor(mindfulresponse_active_weekon,drinksnumber_mindful_response)       845
## cor(drinksnumber_active_weekoff,drinksnumber_mindful_response)         834
## cor(drinksnumber_active_weekon,drinksnumber_mindful_response)          896
## 
## Population-Level Effects: 
##                                                     Estimate Est.Error l-95% CI
## mindfulresponse_Intercept                              -0.21      0.08    -0.38
## drinksnumber_Intercept                                  1.31      0.21     0.92
## mindfulresponse_active_weekon                           0.48      0.12     0.26
## mindfulresponse_regulation_expression                  -0.14      0.08    -0.29
## mindfulresponse_active_weekon:regulation_expression     0.41      0.11     0.17
## drinksnumber_active_weekon                              0.10      0.29    -0.45
## drinksnumber_regulation_expression                     -0.29      0.15    -0.58
## drinksnumber_mindful_response                          -0.59      0.20    -0.98
## drinksnumber_regulation_expression:mindful_response    -0.33      0.20    -0.73
##                                                     u-95% CI Rhat Bulk_ESS
## mindfulresponse_Intercept                              -0.07 1.00      874
## drinksnumber_Intercept                                  1.73 1.00      944
## mindfulresponse_active_weekon                           0.73 1.00      891
## mindfulresponse_regulation_expression                   0.02 1.00      937
## mindfulresponse_active_weekon:regulation_expression     0.63 1.00      937
## drinksnumber_active_weekon                              0.66 1.00      921
## drinksnumber_regulation_expression                      0.01 1.00      964
## drinksnumber_mindful_response                          -0.17 1.00      926
## drinksnumber_regulation_expression:mindful_response     0.08 1.00     1118
##                                                     Tail_ESS
## mindfulresponse_Intercept                                790
## drinksnumber_Intercept                                   907
## mindfulresponse_active_weekon                            935
## mindfulresponse_regulation_expression                    962
## mindfulresponse_active_weekon:regulation_expression      989
## drinksnumber_active_weekon                               874
## drinksnumber_regulation_expression                      1023
## drinksnumber_mindful_response                            980
## drinksnumber_regulation_expression:mindful_response      955
## 
## Family Specific Parameters: 
##                       Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## sigma_mindfulresponse     0.88      0.04     0.81     0.94 1.00      905
## sigma_drinksnumber        2.08      0.09     1.91     2.27 1.00      829
##                       Tail_ESS
## sigma_mindfulresponse      783
## sigma_drinksnumber         947
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

plots

mindful responses by intervention week

slopes_within = ema_within %>%
  select(pID, active_week, mindful_response) %>%
  rename("x" = active_week,
         "predicted" = mindful_response) %>%
  mutate(x = recode(x, "on" = "active", "off" = "control"),
         x = factor(x, levels = c("control", "active"))) %>%
  group_by(pID, x) %>%
  summarize(predicted = mean(predicted, na.rm = TRUE))
  
predicted = ggeffects::ggpredict(fit_brm_m, terms = c("active_week", "regulation_expression [0, 1]")) %>%
  data.frame() %>%
  mutate(x = recode(x, "on" = "active", "off" = "control"),
         group = recode(group, "0" = "mean", "1" = "+1 SD"),
         x = factor(x, levels = c("control", "active")))

(plot_response = predicted %>%
  filter(response.level == "mindfulresponse") %>%
  ggplot(aes(x, predicted)) +
  geom_line(data = slopes_within, aes(x, predicted, group = pID), alpha = .3) +
  geom_line(aes(group = group, color = group), size = 2, , position = position_dodge(.1)) +
  geom_pointrange(aes(ymin = conf.low, ymax = conf.high, color = group), size = 2, linewidth = 2, position = position_dodge(.1)) +
  scale_x_discrete(expand = c(.1, .1)) +
  scale_color_manual(values = palette, name = "signature expression") +
  labs(x = "\nintervention week", y = "within-person mindful response (SD)\n") +
  plot_aes)

alchol consumption ~ mindful responses

vals = seq(-2,2,.2)

points_within = ema_within %>%
  select(pID, drinks_number, mindful_response) %>%
  rename("x" = mindful_response,
         "predicted" = drinks_number)

predicted = ggeffects::ggpredict(fit_brm_m, terms = c("mindful_response", "regulation_expression [0, 1]")) %>%
  data.frame() %>%
  mutate(group = recode(group, "0" = "mean", "1" = "+1 SD"))

(plot_alcohol = predicted %>%
  filter(response.level == "drinksnumber") %>%
  ggplot(aes(x, predicted)) +
  geom_point(data = points_within, alpha = .2, size = 2) +
  geom_line(aes(group = group, color = group), size = 2) +
  geom_ribbon(aes(fill = group, ymin = conf.low, ymax = conf.high), size = 2, alpha = .4) +
  scale_color_manual(values = palette, name = "signature expression") +
  scale_fill_manual(values = palette, name = "signature expression") +
  labs(x = "\nwithin-person mindful response (SD)", y = "within-person number of drinks\n") +
  plot_aes)

combined

ggpubr::ggarrange(plot_response, plot_alcohol, nrow = 1, common.legend = TRUE)

supplementary analyses

Test craving as the mediator instead of mindful responses to alcohol

run model

table

fit_brm_c %>%
  broom.mixed::tidy(conf.int = TRUE) %>%
  filter(effect == "fixed") %>%
  mutate(term = gsub("\\(Intercept\\)", "intercept", term),
         term = gsub("regulation_expression", "signature expression", term),
         term = gsub("active_weekon", "intervention week (active)", term),
         term = gsub("active_weekoff", "intervention week (control)", term),
         term = gsub("craving_previous", "craving rating", term),
         response = gsub("cravingprevious", "craving rating", response),
         response = gsub("drinksnumber", "number of drinks", response),
         term = gsub(":", " x ", term),
         `b [95% CI]` = sprintf("%.2f [%.2f, %.2f]", estimate, conf.low, conf.high)) %>%
  rename("outcome" = response) %>%
  select(outcome, term, `b [95% CI]`) %>%
  arrange(outcome) %>%
  knitr::kable(digits = 2, format = "pandoc")
outcome term b [95% CI]
craving rating intercept -0.02 [-0.09, 0.06]
craving rating intervention week (active) 0.04 [-0.06, 0.14]
craving rating signature expression 0.03 [-0.04, 0.11]
craving rating intervention week (active) x signature expression -0.06 [-0.16, 0.04]
number of drinks intercept 0.04 [-0.06, 0.14]
number of drinks intervention week (active) -0.12 [-0.26, 0.03]
number of drinks signature expression -0.00 [-0.07, 0.06]
number of drinks craving rating 0.30 [0.19, 0.42]
number of drinks signature expression x craving rating 0.06 [-0.07, 0.18]

indirect effect test

hypothesis(
  fit_brm_c,
  'b_drinksnumber_craving_previous * b_cravingprevious_active_weekon + cor_pID__cravingprevious_active_weekon__drinksnumber_active_weekon * sd_pID__cravingprevious_active_weekon * sd_pID__drinksnumber_craving_previous = 0',
  class = NULL,
  seed  =  6523
)
## Hypothesis Tests for class :
##                 Hypothesis Estimate Est.Error CI.Lower CI.Upper Evid.Ratio
## 1 (b_drinksnumber_c... = 0     0.01      0.02    -0.02     0.05         NA
##   Post.Prob Star
## 1        NA     
## ---
## 'CI': 90%-CI for one-sided and 95%-CI for two-sided hypotheses.
## '*': For one-sided hypotheses, the posterior probability exceeds 95%;
## for two-sided hypotheses, the value tested against lies outside the 95%-CI.
## Posterior probabilities of point hypotheses assume equal prior probabilities.

summary

summary(fit_brm_c)
##  Family: MV(gaussian, gaussian) 
##   Links: mu = identity; sigma = identity
##          mu = identity; sigma = identity 
## Formula: craving_previous ~ active_week * regulation_expression + (0 + active_week | i | pID) 
##          drinks_number ~ active_week + regulation_expression * craving_previous + (0 + active_week + craving_previous | i | pID) 
##    Data: ema_within (Number of observations: 1574) 
##   Draws: 4 chains, each with iter = 500; warmup = 250; thin = 4;
##          total post-warmup draws = 250
## 
## Group-Level Effects: 
## ~pID (Number of levels: 34) 
##                                                                   Estimate
## sd(cravingprevious_active_weekoff)                                    0.05
## sd(cravingprevious_active_weekon)                                     0.05
## sd(drinksnumber_active_weekoff)                                       0.11
## sd(drinksnumber_active_weekon)                                        0.10
## sd(drinksnumber_craving_previous)                                     0.30
## cor(cravingprevious_active_weekoff,cravingprevious_active_weekon)    -0.14
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekoff)      -0.01
## cor(cravingprevious_active_weekon,drinksnumber_active_weekoff)       -0.01
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekon)       -0.02
## cor(cravingprevious_active_weekon,drinksnumber_active_weekon)         0.01
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)          -0.33
## cor(cravingprevious_active_weekoff,drinksnumber_craving_previous)    -0.16
## cor(cravingprevious_active_weekon,drinksnumber_craving_previous)      0.14
## cor(drinksnumber_active_weekoff,drinksnumber_craving_previous)       -0.05
## cor(drinksnumber_active_weekon,drinksnumber_craving_previous)         0.06
##                                                                   Est.Error
## sd(cravingprevious_active_weekoff)                                     0.04
## sd(cravingprevious_active_weekon)                                      0.04
## sd(drinksnumber_active_weekoff)                                        0.07
## sd(drinksnumber_active_weekon)                                         0.06
## sd(drinksnumber_craving_previous)                                      0.05
## cor(cravingprevious_active_weekoff,cravingprevious_active_weekon)      0.42
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekoff)        0.40
## cor(cravingprevious_active_weekon,drinksnumber_active_weekoff)         0.40
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekon)         0.41
## cor(cravingprevious_active_weekon,drinksnumber_active_weekon)          0.41
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)            0.42
## cor(cravingprevious_active_weekoff,drinksnumber_craving_previous)      0.38
## cor(cravingprevious_active_weekon,drinksnumber_craving_previous)       0.40
## cor(drinksnumber_active_weekoff,drinksnumber_craving_previous)         0.36
## cor(drinksnumber_active_weekon,drinksnumber_craving_previous)          0.36
##                                                                   l-95% CI
## sd(cravingprevious_active_weekoff)                                    0.00
## sd(cravingprevious_active_weekon)                                     0.00
## sd(drinksnumber_active_weekoff)                                       0.01
## sd(drinksnumber_active_weekon)                                        0.00
## sd(drinksnumber_craving_previous)                                     0.20
## cor(cravingprevious_active_weekoff,cravingprevious_active_weekon)    -0.82
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekoff)      -0.75
## cor(cravingprevious_active_weekon,drinksnumber_active_weekoff)       -0.77
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekon)       -0.77
## cor(cravingprevious_active_weekon,drinksnumber_active_weekon)        -0.73
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)          -0.90
## cor(cravingprevious_active_weekoff,drinksnumber_craving_previous)    -0.80
## cor(cravingprevious_active_weekon,drinksnumber_craving_previous)     -0.68
## cor(drinksnumber_active_weekoff,drinksnumber_craving_previous)       -0.73
## cor(drinksnumber_active_weekon,drinksnumber_craving_previous)        -0.63
##                                                                   u-95% CI Rhat
## sd(cravingprevious_active_weekoff)                                    0.14 1.00
## sd(cravingprevious_active_weekon)                                     0.14 1.00
## sd(drinksnumber_active_weekoff)                                       0.25 1.00
## sd(drinksnumber_active_weekon)                                        0.23 1.00
## sd(drinksnumber_craving_previous)                                     0.41 1.00
## cor(cravingprevious_active_weekoff,cravingprevious_active_weekon)     0.71 1.00
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekoff)       0.77 1.00
## cor(cravingprevious_active_weekon,drinksnumber_active_weekoff)        0.71 1.00
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekon)        0.72 1.00
## cor(cravingprevious_active_weekon,drinksnumber_active_weekon)         0.78 1.00
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)           0.64 1.00
## cor(cravingprevious_active_weekoff,drinksnumber_craving_previous)     0.60 1.00
## cor(cravingprevious_active_weekon,drinksnumber_craving_previous)      0.81 1.00
## cor(drinksnumber_active_weekoff,drinksnumber_craving_previous)        0.65 1.01
## cor(drinksnumber_active_weekon,drinksnumber_craving_previous)         0.71 1.00
##                                                                   Bulk_ESS
## sd(cravingprevious_active_weekoff)                                     897
## sd(cravingprevious_active_weekon)                                      958
## sd(drinksnumber_active_weekoff)                                        643
## sd(drinksnumber_active_weekon)                                         731
## sd(drinksnumber_craving_previous)                                      924
## cor(cravingprevious_active_weekoff,cravingprevious_active_weekon)      858
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekoff)        681
## cor(cravingprevious_active_weekon,drinksnumber_active_weekoff)         920
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekon)         976
## cor(cravingprevious_active_weekon,drinksnumber_active_weekon)          942
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)            677
## cor(cravingprevious_active_weekoff,drinksnumber_craving_previous)      484
## cor(cravingprevious_active_weekon,drinksnumber_craving_previous)       447
## cor(drinksnumber_active_weekoff,drinksnumber_craving_previous)         535
## cor(drinksnumber_active_weekon,drinksnumber_craving_previous)          614
##                                                                   Tail_ESS
## sd(cravingprevious_active_weekoff)                                     882
## sd(cravingprevious_active_weekon)                                      803
## sd(drinksnumber_active_weekoff)                                        641
## sd(drinksnumber_active_weekon)                                         760
## sd(drinksnumber_craving_previous)                                      992
## cor(cravingprevious_active_weekoff,cravingprevious_active_weekon)      952
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekoff)        850
## cor(cravingprevious_active_weekon,drinksnumber_active_weekoff)         915
## cor(cravingprevious_active_weekoff,drinksnumber_active_weekon)         955
## cor(cravingprevious_active_weekon,drinksnumber_active_weekon)          931
## cor(drinksnumber_active_weekoff,drinksnumber_active_weekon)            840
## cor(cravingprevious_active_weekoff,drinksnumber_craving_previous)      619
## cor(cravingprevious_active_weekon,drinksnumber_craving_previous)       776
## cor(drinksnumber_active_weekoff,drinksnumber_craving_previous)         654
## cor(drinksnumber_active_weekon,drinksnumber_craving_previous)          813
## 
## Population-Level Effects: 
##                                                     Estimate Est.Error l-95% CI
## cravingprevious_Intercept                              -0.02      0.04    -0.09
## drinksnumber_Intercept                                  0.04      0.05    -0.06
## cravingprevious_active_weekon                           0.04      0.05    -0.06
## cravingprevious_regulation_expression                   0.03      0.04    -0.04
## cravingprevious_active_weekon:regulation_expression    -0.06      0.05    -0.16
## drinksnumber_active_weekon                             -0.12      0.07    -0.26
## drinksnumber_regulation_expression                     -0.00      0.03    -0.07
## drinksnumber_craving_previous                           0.30      0.06     0.19
## drinksnumber_regulation_expression:craving_previous     0.06      0.06    -0.07
##                                                     u-95% CI Rhat Bulk_ESS
## cravingprevious_Intercept                               0.06 1.00      942
## drinksnumber_Intercept                                  0.14 1.00     1058
## cravingprevious_active_weekon                           0.14 1.00      981
## cravingprevious_regulation_expression                   0.11 1.00     1005
## cravingprevious_active_weekon:regulation_expression     0.04 1.00     1071
## drinksnumber_active_weekon                              0.03 1.00      988
## drinksnumber_regulation_expression                      0.06 1.00     1081
## drinksnumber_craving_previous                           0.42 1.00     1041
## drinksnumber_regulation_expression:craving_previous     0.18 1.00      981
##                                                     Tail_ESS
## cravingprevious_Intercept                                889
## drinksnumber_Intercept                                   867
## cravingprevious_active_weekon                            992
## cravingprevious_regulation_expression                   1034
## cravingprevious_active_weekon:regulation_expression      792
## drinksnumber_active_weekon                               949
## drinksnumber_regulation_expression                       962
## drinksnumber_craving_previous                           1038
## drinksnumber_regulation_expression:craving_previous     1028
## 
## Family Specific Parameters: 
##                       Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## sigma_cravingprevious     1.00      0.02     0.96     1.03 1.00     1115
## sigma_drinksnumber        1.25      0.02     1.21     1.29 1.00     1124
##                       Tail_ESS
## sigma_cravingprevious      917
## sigma_drinksnumber         899
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).